Machine Learning for Kids Worksheet

AI for students lesson 2: How machines learn from examples · Set 49 · 40 questions

AI tip (Show, label, learn): Machine learning learns patterns from many labelled examples — a label is the right answer tag on each example. Good for training: many varied examples, correct labels, every type the model will meet, and separate new data for testing. Bad for training: very few examples, wrong or random labels, only one kind of example, blurry examples, testing on the training data.

1. 1.📚 Good or bad for training a model: blurry, unclear photos? (a) good for training (b) bad for training
2. 2.📚 Good or bad for training a model: new data for testing? (a) bad for training (b) good for training
3. 3.🔍 Which is the odd one out? (a) correct labels (b) photos in many lights (c) clear, sharp examples (d) only one kind of example
4. 4.🔍 Which is the odd one out? (a) only one kind of example (b) correct labels (c) very few examples (d) testing on training data
5. 5.True or false: the message “Send your password to claim a prize” should be labelled “spam”. (a) False (b) True
6. 6.🔍 Which is the odd one out? (a) blurry, unclear photos (b) wrong labels (c) photos in many lights (d) labels added at random
7. 7.📚 Good or bad for training a model: examples of every type? (a) bad for training (b) good for training
8. 8.Which of these is bad for training a model? (a) very few examples (b) checking labels twice (c) new data for testing (d) correct labels
9. 9.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) testing on training data (d) checking labels twice
10. 10.True or false: “testing on training data” is bad for training a model. (a) False (b) True
11. 11.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Earn ₹50,000 a day from home!!!” (a) spam (b) not spam
12. 12.Which of these is bad for training a model? (a) testing on training data (b) correct labels (c) photos in many lights (d) clear, sharp examples
13. 13.🐶 To teach a model to spot dogs in photos, what do you give it? (a) a song about dogs (b) a list of rules only (c) many labelled photos (d) one single photo
14. 14.True or false: the message “Happy birthday! See you at lunch” should be labelled “spam”. (a) True (b) False
15. 15.Which of these is good for training a model? (a) very few examples (b) blurry, unclear photos (c) only one kind of example (d) many varied examples
16. 16.Which of these is good for training a model? (a) new data for testing (b) testing on training data (c) labels added at random (d) wrong labels
17. 17.🔍 Which is the odd one out? (a) wrong labels (b) many varied examples (c) testing on training data (d) labels added at random
18. 18.True or false: the message “The class picnic is on Friday at 8 am” should be labelled “spam”. (a) True (b) False
19. 19.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Please buy milk on the way home” (a) spam (b) not spam
20. 20.🔍 Which is the odd one out? (a) clear, sharp examples (b) very few examples (c) photos in many lights (d) new data for testing
21. 21.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Send your password to claim a prize” (a) not spam (b) spam
22. 22.📚 Good or bad for training a model: photos in many lights? (a) good for training (b) bad for training
23. 23.True or false: “new data for testing” is bad for training a model. (a) True (b) False
24. 24.🔍 Which is the odd one out? (a) clear, sharp examples (b) checking labels twice (c) new data for testing (d) wrong labels
25. 25.Which of these is bad for training a model? (a) copies of one photo (b) photos in many lights (c) examples of every type (d) correct labels
26. 26.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Happy birthday! See you at lunch” (a) spam (b) not spam
27. 27.True or false: “examples of every type” is good for training a model. (a) False (b) True
28. 28.📚 Good or bad for training a model: correct labels? (a) bad for training (b) good for training
29. 29.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Your library book is due on Monday” (a) spam (b) not spam
30. 30.🏷️ What is a “label” in machine learning? (a) a sticker on a laptop (b) the font size (c) the right answer tag (d) the price
31. 31.True or false: “correct labels” is good for training a model. (a) False (b) True
32. 32.True or false: the message “Match practice moved to 5 pm” should be labelled “not spam”. (a) True (b) False
33. 33.True or false: the message “Share your OTP to get cashback” should be labelled “not spam”. (a) True (b) False
34. 34.Which of these is good for training a model? (a) labels added at random (b) copies of one photo (c) only one kind of example (d) correct labels
35. 35.True or false: “wrong labels” is bad for training a model. (a) False (b) True
36. 36.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Match practice moved to 5 pm” (a) not spam (b) spam
37. 37.True or false: “copies of one photo” is bad for training a model. (a) False (b) True
38. 38.🏷️ You are labelling messages to train a spam filter. How should this one be labelled? “Last chance! Free gift card inside” (a) spam (b) not spam
39. 39.📚 Good or bad for training a model: many varied examples? (a) bad for training (b) good for training
40. 40.🔍 Which is the odd one out? (a) many varied examples (b) correct labels (c) clear, sharp examples (d) copies of one photo

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